ImageNet [1]} is a large-scale dataset which contains over 1M training images and 50K test images collecting from 1000 categories.
We adopt ResNet and MobileNet V2 to validate the effectiveness.
For ResNet, we set the initial learning rate to 0.2 and drop it by 0.1 at 20K, 40K, 60K iterations and terminate at 65K iterations.
Weight decay is set to 1e-4 and batch size is 2048 with 32 GPUs.
As for MobileNetV2, the learning rate starts at 0.1 and drops by 0.1 at 45K, 75K, and 100K iterations with 130K iterations in total.
